Article Per Year (5 Year)
p-Index From 2020 - 2025
0.659
P-Index
This Author published in this journals
All Journal Jurnal Teknik Informatika (JUTIF) BEES: Bulletin of Electrical and Electronics Engineering Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Amalya, Nanda
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Sistem Penyiram Otomatis Berbasis IOT Smart Home Pada Tanaman Rumah Menggunakan Arduino Atmega 328P Nainggolan, Joshua Fines; Poningsih, Poningsih; Irawan, Irawan; Irawan, Eka; Amalya, Nanda
BEES: Bulletin of Electrical and Electronics Engineering Vol 4 No 2 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bees.v4i2.4637

Abstract

A greenhouse is a building with a frame or shaped like bubbles, covered with clear or translucent material that can transmit light optimally for production and protect plants from climatic conditions that are detrimental to plant growth. Research on an Arduino-based plant watering system in a plant house aims to design, create, and test a system to be able to carry out watering. The method used in research on an IOT smartphone-based plant watering system uses an ATMEGA 328P Arduino. There are several stages that need to be paid attention to, namely the design stage, the construction/manufacturing stage, and the installation stage. Next is the testing of products that have been made using Arduino and ESP8266. Watering can be scheduled so that it is done on time. The system can do watering; watering is done automatically with a working voltage of 208–214 VAC and 15 VDC and a constant Arduino pin voltage of 4.8 VDC. By carrying out tests on watering plants, based on the test results, the Arduino-based automatic plant watering system in the plant house can work well according to design.
Perbandingan Algoritma Decision Tree, ID3, dan Random Forest dalam Klasifikasi Faktor-Faktor yang Mempengaruhi Karier Mahasiswa Ilmu Komputer Hartama, Dedy; Amalya, Nanda
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 1 (2025): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v6i1.1113

Abstract

This study aims to compare the performance of three classification algorithms, namely Decision Tree, ID3, and Random Forest, in identifying factors that influence the careers of computer Science students. These algorithms are applied to a dataset that includes various student attributes, such as GPA, programming skills, and completed projects. The results show that Random Forest provides more accurate and stable prediction results than Decision Tree and ID3, especially in reducing the risk of overfitting. Students with high skills in Python and SQL and who focus on software development tend to choose a career in Software Engineering. While those involved in AI/ML-based projects tend to choose Data Science. The conclusions of this study provide valuable insights for educational institutions to design more effective career development strategies for students.
POLAK-RIBIERE CONJUGATE GRADIENT ALGORITHM IN PREDICTING THE PERCENTAGE OF OPEN UNEMPLOYMENT IN NORTH SUMATRA PROVINCE Amalya, Nanda; Solikhun, Solikhun
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 1 (2024): JUTIF Volume 5, Number 1, February 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.1.1047

Abstract

The economic problem that has a direct impact on human life and welfare is unemployment. One of the cities in Indonesia with the highest unemployment rate is North Sumatra Province. For example, Tebing Tinggi City had the highest unemployment rate of 9.73% in 2017, while Nias Selatan had the lowest percentage of 0.31%. This research is important to do in order to anticipate the unemployment rate in North Sumatra for any party, be it the government or the private sector, so that they can work together to overcome the problem of unemployment in the future which is the main problem in the economy. For example, the government creates programs to help reduce the number of unemployed, provide preparation or do other things, helping people to become more imaginative and have skills so they can compete in the world market. Predicting unemployment has been the subject of many studies, one of which is by utilizing artificial neural networks. This study aims to predict the percentage of unemployed in North Sumatra from 2022 to 2026, using the Backpropagation Neural Network Algorithm, the Conjugate Gradient Polak-Ribiere method and Matlab version 2011 for research and data analysis. This research utilizes open action rate stimulation data for the population of North Sumatra based on residents aged over 15 years from 2017 to 2021. Using five architectural models, namely: 4-50-1, 4-55-1, 4-70- 1, 4-75-1, and 4-77-1. The final results were obtained using the most accurate architectural model, namely model 4-75-1 which has a Mean Squared Error (MSE) of 0.0000004288 and an accuracy rate of 100% with a time of 00.09 at epoch 452.
Co-Authors Eka Irawan Hartama, Dedy Irawan Irawan Nainggolan, Joshua Fines Poningsih Poningsih, Poningsih Solikhun Solikhun, Solikhun